bachelor thesis
0juliat0
2023-11-30
Libraries
Load data
file_path_t <- "~/rocker/RDEB/ccc_cellchat.t.2.rds"
cellchat.t <- readRDS(file_path_t)
file_path_s <- "~/rocker/RDEB/ccc_cellchat.s.2.rds"
cellchat.s <- readRDS(file_path_s)Circle diagramm for skin, SCC
cellchat.t@netP$pathways## [1] "COLLAGEN" "LAMININ" "MIF" "MHC-I" "FN1"
## [6] "CD99" "THBS" "VISFATIN" "MHC-II" "APP"
## [11] "CLEC" "MK" "ADGRE5" "GALECTIN" "CXCL"
## [16] "TGFb" "PARs" "SEMA4" "PTPRM" "SEMA3"
## [21] "TENASCIN" "CD45" "ANNEXIN" "PTN" "ICAM"
## [26] "ITGB2" "GAS" "EGF" "PECAM1" "ANGPTL"
## [31] "TNF" "CD22" "JAM" "CD46" "VEGF"
## [36] "NOTCH" "THY1" "PERIOSTIN" "CCL" "SELE"
## [41] "MPZ" "ncWNT" "NEGR" "ALCAM" "CD6"
## [46] "ANGPT" "NECTIN" "COMPLEMENT" "VCAM" "SELL"
## [51] "FGF" "PDGF" "PROS" "CADM" "HSPG"
## [56] "CALCR" "CD226" "BAFF" "CD86" "NCAM"
## [61] "IL16" "IL1" "SEMA6" "EPHB" "BMP"
## [66] "EPHA" "LCK" "TIGIT" "IFN-II" "GRN"
## [71] "ESAM" "NRXN" "KIT" "CDH5" "CSF"
## [76] "SELPLG" "CDH" "EDN" "BTLA" "IL2"
## [81] "CNTN" "CD70" "TWEAK" "IGF" "APRIL"
## [86] "TRAIL" "VISTA" "NRG" "APJ" "RELN"
## [91] "IL6" "CD34" "HGF" "L1CAM" "SN"
## [96] "CD137" "WNT"pathways.show.t <- c("COLLAGEN", "LAMININ", "MIF", "MHC-I", "FN1", "CD99", "THBS", "VISFATIN", "MHC-II", "APP", "CLEC", "MK", "ADGRE5", "GALECTIN", "CXCL", "TGFb", "PARs", "SEMA4", "PTPRM", "SEMA3", "TENASCIN", "CD45", "ANNEXIN", "PTN", "ICAM", "ITGB2", "GAS", "EGF", "PECAM1", "ANGPTL", "TNF", "CD22", "JAM", "CD46", "VEGF", "NOTCH", "THY1", "PERIOSTIN", "CCL", "SELE", "MPZ", "ncWNT", "NEGR", "ALCAM", "CD6", "ANGPT", "NECTIN", "COMPLEMENT", "VCAM", "SELL", "FGF", "PDGF", "PROS", "CADM", "HSPG", "CALCR", "CD226", "BAFF", "CD86", "NCAM", "IL16", "IL1", "SEMA6", "EPHB", "BMP", "EPHA", "LCK", "TIGIT", "IFN-II", "GRN", "ESAM", "NRXN", "KIT", "CDH5", "CSF", "SELPLG", "CDH", "EDN", "BTLA", "IL2", "CNTN", "CD70", "TWEAK", "IGF", "APRIL", "TRAIL", "VISTA", "NRG", "APJ", "RELN", "IL6", "CD34", "HGF", "L1CAM", "SN", "CD137", "WNT")
cellchat.s@netP$pathways## [1] "COLLAGEN" "LAMININ" "MHC-I" "MIF" "FN1"
## [6] "CD99" "THBS" "VISFATIN" "CLEC" "APP"
## [11] "ADGRE5" "MHC-II" "CXCL" "ICAM" "SELE"
## [16] "MK" "CD45" "PTN" "PTPRM" "ITGB2"
## [21] "PARs" "CD22" "ALCAM" "CD6" "TGFb"
## [26] "ANGPTL" "VEGF" "JAM" "CD46" "ANNEXIN"
## [31] "PECAM1" "GAS" "FGF" "SEMA3" "MPZ"
## [36] "CADM" "NOTCH" "TENASCIN" "VCAM" "NEGR"
## [41] "PERIOSTIN" "NECTIN" "IL6" "ANGPT" "SEMA4"
## [46] "THY1" "EGF" "TIGIT" "TNF" "PDGF"
## [51] "CCL" "SEMA7" "CALCR" "NCAM" "IL2"
## [56] "ncWNT" "IFN-II" "EPHA" "PROS" "IL16"
## [61] "LCK" "EPHB" "CD226" "HSPG" "SELL"
## [66] "KIT" "BMP" "ESAM" "CD70" "CDH5"
## [71] "LIGHT" "CD86" "DESMOSOME" "BAFF" "SEMA6"
## [76] "TRAIL" "COMPLEMENT" "IGF" "CDH1" "SELPLG"
## [81] "IL1" "FASLG" "EDN" "TWEAK" "NRXN"
## [86] "IL10" "CD34" "CSF3" "LIFR" "CSF"
## [91] "NRG" "L1CAM" "CDH" "WNT" "VEGI"pathways.show.s <- c("COLLAGEN", "LAMININ", "MHC-I", "MIF", "FN1", "CD99", "THBS", "VISFATIN", "CLEC", "APP", "ADGRE5", "MHC-II", "CXCL", "ICAM", "SELE", "MK", "CD45", "PTN", "PTPRM", "ITGB2", "PARs", "CD22", "ALCAM", "CD6", "TGFb", "ANGPTL", "VEGF", "JAM", "CD46", "ANNEXIN", "PECAM1", "GAS", "FGF", "SEMA3", "MPZ", "CADM", "NOTCH", "TENASCIN", "VCAM", "NEGR", "PERIOSTIN", "NECTIN", "IL6", "ANGPT", "SEMA4", "THY1", "EGF", "TIGIT", "TNF", "PDGF", "CCL", "SEMA7", "CALCR", "NCAM", "IL2", "ncWNT", "IFN-II", "EPHA", "PROS", "IL16", "LCK", "EPHB", "CD226", "HSPG", "SELL", "KIT", "BMP", "ESAM", "CD70", "CDH5", "LIGHT", "CD86", "DESMOSOME", "BAFF", "SEMA6", "TRAIL", "COMPLEMENT", "IGF", "CDH1", "SELPLG", "IL1", "FASLG", "EDN", "TWEAK", "NRXN", "IL10", "CD34", "CSF3", "LIFR", "CSF", "NRG", "L1CAM", "CDH", "WNT", "VEGI")
# Output PDF setup
pdf("~/rocker/RDEB/thesis/Chord_diagram_SCC.pdf")
netVisual_aggregate(cellchat.t, signaling = pathways.show.t, layout = "chord")
# Output PDF setup
pdf("~/rocker/RDEB/thesis/Chord_diagram_Skin.pdf")
netVisual_aggregate(cellchat.s, signaling = pathways.show.s, layout = "chord")Heatmap SCC, heatmap skin
# Set up PDF output for SCC, saving directly to the desired directory
pdf("~/rocker/RDEB/thesis/Heatmap_SCC_Interaction_count.pdf", width = 16, height = 8)
# Interaction count heatmap for SCC
gg1_tumor <- netVisual_heatmap(cellchat.t, measure = "count")## Do heatmap based on a single objectplot(gg1_tumor)
# Set up PDF output for Skin, also saving directly to the desired directory
pdf("~/rocker/RDEB/thesis/Heatmap_Skin_Interaction_count.pdf", width = 16, height = 8)
# Interaction count heatmap for Skin
gg1_skin <- netVisual_heatmap(cellchat.s, measure = "count")## Do heatmap based on a single objectplot(gg1_skin)There are no T naive CD4 in skin so lets exclude them from analysis
# Define the identifier for naive CD4 T cells
naive_CD4_identifier <- "T naive CD4"
# Filter out interactions involving naive CD4 T cells from the SCC dataset
cellchat.t.sC <- subsetCommunication(cellchat.t, thresh=1) %>%
filter(!(source == naive_CD4_identifier |
target == naive_CD4_identifier))
# Filter out interactions involving naive CD4 T cells from the skin dataset
cellchat.s.sC <- subsetCommunication(cellchat.s, thresh=1) %>%
filter(!(source == naive_CD4_identifier |
target == naive_CD4_identifier))
# merge the two data frames
merged_data <- merge(cellchat.t.sC, cellchat.s.sC,
by = c("source", "target", "ligand", "receptor",
"interaction_name","interaction_name_2",
"pathway_name", "annotation", "evidence"),
all = TRUE)Replace NA values with 0
merged_data <- merged_data %>%
mutate(
prob.t = ifelse(is.na(prob.x), 0, prob.x),
prob.s = ifelse(is.na(prob.y), 0, prob.y),
pval.t = ifelse(is.na(pval.x), 0, pval.x),
pval.s = ifelse(is.na(pval.y), 0, pval.y)
) %>%
select(-prob.x, -prob.y, -pval.x, -pval.y) # delete columns Calculating the difference between probabilities SCC - skin
merged_data <- merged_data %>%
mutate(prob.delta = prob.t - prob.s) %>%
arrange(desc(abs(prob.delta)))Count interactions for skin and SCC (actual numeric difference )
# Create the summary data frame with the desired columns
merged_df.interactions <- merged_data %>%
group_by(source, target) %>%
summarise(
Tumor_Interactions = sum(prob.t > 0),
Skin_Interactions = sum(prob.s > 0),
Interaction_Difference = Tumor_Interactions - Skin_Interactions,
Interaction_Difference_abs = sum(xor(prob.t == 0, prob.s == 0)),
.groups = 'drop'
)
# Print the interaction summary data frame
print(merged_df.interactions)## # A tibble: 688 × 6
## source target Tumor_Interactions Skin_Interactions Interaction_Difference
## <fct> <fct> <int> <int> <int>
## 1 B cell B cell 8 10 -2
## 2 B cell Endothel 14 7 7
## 3 B cell Endothel_… 20 28 -8
## 4 B cell Fibroblas… 17 22 -5
## 5 B cell Fibroblas… 8 10 -2
## 6 B cell Fibroblas… 3 2 1
## 7 B cell Fibroblas… 19 17 2
## 8 B cell Fibroblas… 15 30 -15
## 9 B cell T gd 12 20 -8
## 10 B cell Keratinoc… 9 17 -8
## # ℹ 678 more rows
## # ℹ 1 more variable: Interaction_Difference_abs <int>Bubble plot based on counts difference
# Create a point plot with color and size adjustments
point_plot <- ggplot(merged_df.interactions, aes(x = target, y = source)) +
geom_point(aes(size = Interaction_Difference_abs, color = Interaction_Difference), shape = 20) +
scale_size_continuous(name = "Absolute Interaction Difference", range = c(1, 11)) +
scale_color_gradient2(name = "Interactions Difference",
high = rgb(178/255, 24/255, 43/255),
mid = "white",
low = rgb(33/255, 102/255, 172/255),
midpoint = 0) + # Diverging color scale
labs(title = "Difference in Number of Interactions (SCC vs Skin)",
x = "Target cells (receptor)",
y = "Source cells (ligand)",
color = "Interactions Difference",
size = "Abs Interaction Diff") +
theme_minimal() +
theme(
axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1, size = 10),
axis.text.y = element_text(size = 10),
axis.title = element_text(size = 12),
plot.title = element_text(size = 14, face = "bold"),
legend.position = "right",
legend.direction = "vertical",
legend.title = element_text(size = 12),
legend.text = element_text(size = 10)
)
# Print the point plot
print(point_plot)
# Save the plot
ggsave("~/rocker/RDEB/thesis/bubble_plot_based_on_interactions_difference.png",
plot = point_plot,
width = 10,
height = 8,
dpi = 300)Number of interactions per source cell (ligand) in SCC - skin
# Compute interaction counts for each dataset, excluding T naive CD4
df.t <- cellchat.t %>%
subsetCommunication(thresh = NA) %>%
filter(source != naive_CD4_identifier & target != naive_CD4_identifier) %>%
dplyr::as_tibble() %>%
dplyr::count(source) %>%
dplyr::rename(Tumor_Interactions = n)
df.s <- cellchat.s %>% # no need to exclude, since in skin there is nothing
subsetCommunication(thresh = NA) %>%
dplyr::as_tibble() %>%
dplyr::count(source) %>%
dplyr::rename(Skin_Interactions = n)
# Merge datasets by the 'source' (27 levels - celltypes) column
combined_data.diff <- full_join(df.t, df.s, by = "source")
# Remove NA values because T naive CD4 in Skin_Interactions = NA
combined_data.diff$Tumor_Interactions[
is.na(combined_data.diff$Tumor_Interactions)
] <- 0
combined_data.diff$Skin_Interactions[
is.na(combined_data.diff$Skin_Interactions)
] <- 0
# Compute the difference for each source: skin - SCC
combined_data.diff$Interaction_Difference <-
combined_data.diff$Tumor_Interactions - combined_data.diff$Skin_Interactions
# Display the table (screenshot saved)
print(combined_data.diff, n = 27)# Display the table (screenshot saved)## # A tibble: 27 × 4
## source Tumor_Interactions Skin_Interactions Interaction_Difference
## <fct> <dbl> <dbl> <dbl>
## 1 B cell 363 456 -93
## 2 Endothel 884 638 246
## 3 Endothel_vasc._31 1071 860 211
## 4 Erythrocyte 88 92 -4
## 5 Fibroblast_18 1152 1100 52
## 6 Fibroblast_20 993 813 180
## 7 Fibroblast_25 551 458 93
## 8 Fibroblast_32 1299 1002 297
## 9 Fibroblast_36 1116 1241 -125
## 10 T gd 260 300 -40
## 11 Keratinocyte_26 551 615 -64
## 12 Mast_27 154 127 27
## 13 Monocyte 451 352 99
## 14 Monocyte_23 276 175 101
## 15 Neurons_47 25 174 -149
## 16 Neutrophil 105 157 -52
## 17 NK 239 346 -107
## 18 NK T like 293 242 51
## 19 Plasma_15 301 329 -28
## 20 Plasma_35 62 165 -103
## 21 Plasma_37 284 313 -29
## 22 Schwann_43 813 803 10
## 23 T cytotox. CD8 266 329 -63
## 24 T fh 536 504 32
## 25 T mem 1 211 266 -55
## 26 T mem 2 250 309 -59
## 27 T reg CD4 230 289 -59Scatter plot source
scatter_plot <- ggplot(
combined_data.diff,
aes(x = Tumor_Interactions,
y = Skin_Interactions,
label = source)) +
geom_point(
aes(color = source), size = 3
) +
geom_text(
aes(label = source), size = 3
) +
geom_smooth(
method = "lm",
se = TRUE
) +
labs(
title = "Number of Interactions per source Cell",
x = "SCC Interactions",
y = "Skin Interactions"
) +
theme(legend.position = "none")+
theme_minimal()
print(scatter_plot)## `geom_smooth()` using formula = 'y ~ x'## Warning: The following aesthetics were dropped during statistical transformation: label.
## ℹ This can happen when ggplot fails to infer the correct grouping structure in
## the data.
## ℹ Did you forget to specify a `group` aesthetic or to convert a numerical
## variable into a factor?
ggsave("~/rocker/RDEB/thesis/scatter_plot_source.png",
plot = scatter_plot,
width = 10,
height = 8,
dpi = 300)## `geom_smooth()` using formula = 'y ~ x'## Warning: The following aesthetics were dropped during statistical transformation: label.
## ℹ This can happen when ggplot fails to infer the correct grouping structure in
## the data.
## ℹ Did you forget to specify a `group` aesthetic or to convert a numerical
## variable into a factor?Number of interactions per target cell (receptor) in SCC - skin
# Compute interaction counts for each dataset
df.t <- cellchat.t %>%
subsetCommunication(thresh = NA) %>%
filter(source != naive_CD4_identifier & target != naive_CD4_identifier) %>%
dplyr::as_tibble() %>%
dplyr::count(target) %>%
dplyr::rename(Tumor_Interactions = n)
df.s <- cellchat.s %>%
subsetCommunication(thresh = NA) %>%
dplyr::as_tibble() %>%
dplyr::count(target) %>%
dplyr::rename(Skin_Interactions = n)
# Merge datasets by the 'target' (27 levels - celltypes) column
combined_data.diff <- full_join(
df.t,
df.s,
by = "target")
# Remove NA values because T naive CD4 in Skin_Interactions = NA
combined_data.diff$Tumor_Interactions[
is.na(combined_data.diff$Tumor_Interactions)
] <- 0
combined_data.diff$Skin_Interactions[
is.na(combined_data.diff$Skin_Interactions)
] <- 0
# Compute the difference for each target: SCC - skin
combined_data.diff$Interaction_Difference <-
combined_data.diff$Tumor_Interactions - combined_data.diff$Skin_Interactions
print (combined_data.diff, n = 27) # Display the table (screenshot saved)## # A tibble: 26 × 4
## target Tumor_Interactions Skin_Interactions Interaction_Difference
## <fct> <dbl> <dbl> <dbl>
## 1 B cell 293 333 -40
## 2 Endothel 581 291 290
## 3 Endothel_vasc._31 915 929 -14
## 4 Fibroblast_18 764 659 105
## 5 Fibroblast_20 561 428 133
## 6 Fibroblast_25 188 152 36
## 7 Fibroblast_32 852 575 277
## 8 Fibroblast_36 709 976 -267
## 9 T gd 324 505 -181
## 10 Keratinocyte_26 611 705 -94
## 11 Mast_27 300 183 117
## 12 Monocyte 827 569 258
## 13 Monocyte_23 193 196 -3
## 14 Neurons_47 25 162 -137
## 15 Neutrophil 275 257 18
## 16 NK 539 691 -152
## 17 NK T like 235 282 -47
## 18 Plasma_15 511 542 -31
## 19 Plasma_35 283 168 115
## 20 Plasma_37 492 535 -43
## 21 Schwann_43 686 595 91
## 22 T cytotox. CD8 596 588 8
## 23 T fh 748 867 -119
## 24 T mem 1 416 339 77
## 25 T mem 2 442 448 -6
## 26 T reg CD4 458 480 -22Scatter plot target
scatter_plot <- ggplot(combined_data.diff,
aes(
x = Tumor_Interactions,
y = Skin_Interactions,
label = target)
) +
geom_point(aes(color = target), size = 3) +
geom_text(aes(label = target), size = 3) +
geom_smooth(method = "lm",se = TRUE) +
labs(
title = "Number of Interactions per target Cell",
x = "SCC Interactions",
y = "Skin Interactions"
) +
theme(legend.position = "none")+
theme_minimal()
print(scatter_plot)## `geom_smooth()` using formula = 'y ~ x'## Warning: The following aesthetics were dropped during statistical transformation: label.
## ℹ This can happen when ggplot fails to infer the correct grouping structure in
## the data.
## ℹ Did you forget to specify a `group` aesthetic or to convert a numerical
## variable into a factor?
ggsave("~/rocker/RDEB/thesis/scatter_plot_target.png",
plot = scatter_plot,
width = 10,
height = 8,
dpi = 300)## `geom_smooth()` using formula = 'y ~ x'## Warning: The following aesthetics were dropped during statistical transformation: label.
## ℹ This can happen when ggplot fails to infer the correct grouping structure in
## the data.
## ℹ Did you forget to specify a `group` aesthetic or to convert a numerical
## variable into a factor?Plotting top 10 interactions with biggest differences in SCC - skin
# Combining data SCC and skin
df.t <- cellchat.t %>%
subsetCommunication(thresh = NA) %>%
filter(source != naive_CD4_identifier & target != naive_CD4_identifier) %>%
dplyr::as_tibble() %>%
dplyr::group_by(source, target) %>%
dplyr::summarise(Tumor_Interactions = n())## `summarise()` has grouped output by 'source'. You can override using the
## `.groups` argument.df.s <- cellchat.s %>%
subsetCommunication(thresh = NA) %>%
dplyr::as_tibble() %>%
dplyr::group_by(source, target) %>%
dplyr::summarise(Skin_Interactions = n())## `summarise()` has grouped output by 'source'. You can override using the
## `.groups` argument.# Merge datasets by the 'source' and 'target'
combined_data.diff <- full_join(
df.t,
df.s,
by = c("source", "target")
)
# Replace NAs with 0
combined_data.diff$Tumor_Interactions[
is.na(combined_data.diff$Tumor_Interactions)
] <- 0
combined_data.diff$Skin_Interactions[
is.na(combined_data.diff$Skin_Interactions)
] <- 0
# Compute the difference for each source-target pair: skin - SCC
combined_data.diff$Interaction_Difference <-
combined_data.diff$Tumor_Interactions - combined_data.diff$Skin_Interactions
# Filter to get the top 10 interactions by absolute difference
top_10_diff <- combined_data.diff %>%
dplyr::ungroup() %>% # Calculate differences without grouping by 'source'
dplyr::arrange(-abs(Interaction_Difference)) %>%
dplyr::slice_head(n = 10)
print(top_10_diff)## # A tibble: 10 × 5
## source target Tumor_Interactions Skin_Interactions Interaction_Difference
## <fct> <fct> <dbl> <dbl> <dbl>
## 1 Fibroblas… Fibro… 88 47 41
## 2 Fibroblas… Fibro… 71 111 -40
## 3 Fibroblas… Endot… 59 21 38
## 4 Endothel_… Fibro… 80 43 37
## 5 Fibroblas… Monoc… 79 43 36
## 6 Fibroblas… Endot… 49 16 33
## 7 Fibroblas… Fibro… 73 42 31
## 8 Fibroblas… Endot… 53 23 30
## 9 Fibroblas… Fibro… 63 93 -30
## 10 Endothel Endot… 44 15 29# Plot top 10 interactions with biggest differences
difference_plot <- ggplot(
top_10_diff,
aes(
x = paste(source, target, sep = "-"),
y = Interaction_Difference,
fill = Interaction_Difference > 0)
) +
geom_bar(
stat = "identity",
position = "dodge"
) +
scale_fill_manual(
values = c(
"TRUE" = rgb(178/255, 24/255, 43/255),
"FALSE" = rgb(33/255, 102/255, 172/255)
),
labels = c(
"TRUE" = "SCC",
"FALSE" = "Skin")
) +
theme_minimal() +
labs(
title = "Top 10 Differences in Interactions (SCC - Skin)",
y = "Difference in Interactions",
x = "Interaction (Source-target)") +
theme(axis.text.x = element_text(
angle = 90,
hjust = 1)
)
print(difference_plot)
ggsave("~/rocker/RDEB/thesis/Top_10_Differences_in_Interactions.png",
plot = difference_plot,
width = 10,
height = 8,
dpi = 300)Function to process interactions between sorce and target celltypes
plot_interaction <- function(
df,
source_value,
target_value) {
df_filtered <- df %>%
filter(source == source_value & target == target_value) %>%
slice_max(
order_by = abs(prob.delta),
n = 40) %>%
select(-c(pval.t, pval.s))
# Create a label from the source and target values
interaction_label <- paste(
source_value,
target_value,
sep = " to ")
# Pivot and plot using the new label
df_filtered %>%
pivot_longer(cols = c("prob.s", "prob.t"),
names_to = "variable",
values_to = "value") %>%
ggplot(aes(
x = interaction_name_2,
y = value,
fill = variable)
) +
geom_col(position = "dodge") +
scale_fill_manual(
values = c(
"prob.s" = rgb(33/255, 102/255, 172/255),
"prob.t" = rgb(178/255, 24/255, 43/255)
)
) +
labs(
x = interaction_label,
y = "Probability Delta",
fill = "Probability"
) +
theme(axis.text.x = element_text(
angle = 90,
hjust = 1,
vjust = 0.5)
)
}Interaction based on cell types
# Now, let's loop over these top 10 interactions and create the desired plots.
for (i in 1:nrow(top_10_diff)) {
current_source <- top_10_diff$source[i]
current_target <- top_10_diff$target[i]
# Filter the merged_data for the current pair.
current_data <- merged_data %>%
filter(source == current_source,
target == current_target)
# Plot
p <- ggplot(
current_data,
aes(
x = ligand,
y = receptor,
fill = prob.delta)
) +
geom_tile() +
scale_fill_gradient2(
low = rgb(33/255, 102/255, 172/255),
high = rgb(178/255, 24/255, 43/255),
mid = "grey",
midpoint = 0,
limits = c(min(current_data$prob.delta, na.rm = TRUE),
max(current_data$prob.delta, na.rm = TRUE)),
name = "Prob Delta") +
labs(title = paste("Ligand-Receptor Interactions for",
current_source,
"to",
current_target),
x = "Ligand",
y = "Receptor"
) +
theme_minimal() +
theme(axis.text.x = element_text(
angle = 90,
vjust = 0.5
),
axis.text.y = element_text(hjust = 1))
print(p)
# Save the plot
file_name <- paste0("~/rocker/RDEB/thesis/interaction_plots/",
current_source,
"_to_",
current_target,
".pdf"
)
ggsave(
file_name,
plot = p,
width = 10,
height = 10
)
# Extracting the relevant interactions from merged_data for the current interaction pair
filtered_data <- current_data %>%
distinct(pathway_name) # Getting unique pathway names involved in these interactions
# Print the pathways involved in the current interaction pair
cat("Pathways for interaction", current_source, "to", current_target, ":\n")
print(filtered_data)
# Check if these pathways are in the provided pathways lists
pathways_involved_t <- filtered_data$pathway_name %in% pathways.show.t
pathways_involved_s <- filtered_data$pathway_name %in% pathways.show.s
# Print pathways involved both in tumor and skin for the current interaction pair
cat("Pathways in Tumor:\n")
print(filtered_data$pathway_name[pathways_involved_t])
cat("Pathways in Skin:\n")
print(filtered_data$pathway_name[pathways_involved_s])
}
## Pathways for interaction 8 to 8 :
## pathway_name
## 1 COLLAGEN
## 2 NEGR
## 3 MK
## 4 LAMININ
## 5 TENASCIN
## 6 SEMA4
## 7 FN1
## 8 VISFATIN
## 9 FGF
## 10 THBS
## 11 ncWNT
## 12 ANGPTL
## 13 TGFb
## 14 GAS
## 15 CD99
## 16 PTPRM
## 17 JAM
## 18 CXCL
## 19 PERIOSTIN
## 20 SEMA3
## 21 PROS
## 22 CADM
## 23 PDGF
## 24 CNTN
## 25 PTN
## 26 NECTIN
## 27 TWEAK
## 28 BMP
## 29 MIF
## 30 MPZ
## 31 IGF
## 32 WNT
## Pathways in Tumor:
## [1] "COLLAGEN" "NEGR" "MK" "LAMININ" "TENASCIN" "SEMA4"
## [7] "FN1" "VISFATIN" "FGF" "THBS" "ncWNT" "ANGPTL"
## [13] "TGFb" "GAS" "CD99" "PTPRM" "JAM" "CXCL"
## [19] "PERIOSTIN" "SEMA3" "PROS" "CADM" "PDGF" "CNTN"
## [25] "PTN" "NECTIN" "TWEAK" "BMP" "MIF" "MPZ"
## [31] "IGF" "WNT"
## Pathways in Skin:
## [1] "COLLAGEN" "NEGR" "MK" "LAMININ" "TENASCIN" "SEMA4"
## [7] "FN1" "VISFATIN" "FGF" "THBS" "ncWNT" "ANGPTL"
## [13] "TGFb" "GAS" "CD99" "PTPRM" "JAM" "CXCL"
## [19] "PERIOSTIN" "SEMA3" "PROS" "CADM" "PDGF" "PTN"
## [25] "NECTIN" "TWEAK" "BMP" "MIF" "MPZ" "IGF"
## [31] "WNT"
## Pathways for interaction 9 to 9 :
## pathway_name
## 1 COLLAGEN
## 2 ANGPTL
## 3 LAMININ
## 4 MK
## 5 THBS
## 6 MPZ
## 7 VISFATIN
## 8 JAM
## 9 NEGR
## 10 IL6
## 11 SEMA3
## 12 FN1
## 13 SEMA4
## 14 FGF
## 15 GAS
## 16 TENASCIN
## 17 ADGRE5
## 18 PROS
## 19 CXCL
## 20 NOTCH
## 21 CD46
## 22 NECTIN
## 23 PTN
## 24 TWEAK
## 25 CD99
## 26 PERIOSTIN
## 27 HSPG
## 28 PTPRM
## 29 EPHA
## 30 TGFb
## 31 PDGF
## 32 EPHB
## 33 CADM
## 34 MIF
## 35 IGF
## 36 WNT
## Pathways in Tumor:
## [1] "COLLAGEN" "ANGPTL" "LAMININ" "MK" "THBS" "MPZ"
## [7] "VISFATIN" "JAM" "NEGR" "IL6" "SEMA3" "FN1"
## [13] "SEMA4" "FGF" "GAS" "TENASCIN" "ADGRE5" "PROS"
## [19] "CXCL" "NOTCH" "CD46" "NECTIN" "PTN" "TWEAK"
## [25] "CD99" "PERIOSTIN" "HSPG" "PTPRM" "EPHA" "TGFb"
## [31] "PDGF" "EPHB" "CADM" "MIF" "IGF" "WNT"
## Pathways in Skin:
## [1] "COLLAGEN" "ANGPTL" "LAMININ" "MK" "THBS" "MPZ"
## [7] "VISFATIN" "JAM" "NEGR" "IL6" "SEMA3" "FN1"
## [13] "SEMA4" "FGF" "GAS" "TENASCIN" "ADGRE5" "PROS"
## [19] "CXCL" "NOTCH" "CD46" "NECTIN" "PTN" "TWEAK"
## [25] "CD99" "PERIOSTIN" "HSPG" "PTPRM" "EPHA" "TGFb"
## [31] "PDGF" "EPHB" "CADM" "MIF" "IGF" "WNT"
## Pathways for interaction 8 to 2 :
## pathway_name
## 1 COLLAGEN
## 2 LAMININ
## 3 MK
## 4 VISFATIN
## 5 MIF
## 6 FN1
## 7 CXCL
## 8 SEMA4
## 9 CALCR
## 10 ANGPTL
## 11 CD46
## 12 CCL
## 13 PTN
## 14 ncWNT
## 15 VEGF
## 16 PTPRM
## 17 CD99
## 18 SEMA3
## 19 NECTIN
## 20 APJ
## 21 PDGF
## 22 APP
## 23 IGF
## Pathways in Tumor:
## [1] "COLLAGEN" "LAMININ" "MK" "VISFATIN" "MIF" "FN1"
## [7] "CXCL" "SEMA4" "CALCR" "ANGPTL" "CD46" "CCL"
## [13] "PTN" "ncWNT" "VEGF" "PTPRM" "CD99" "SEMA3"
## [19] "NECTIN" "APJ" "PDGF" "APP" "IGF"
## Pathways in Skin:
## [1] "COLLAGEN" "LAMININ" "MK" "VISFATIN" "MIF" "FN1"
## [7] "CXCL" "SEMA4" "CALCR" "ANGPTL" "CD46" "CCL"
## [13] "PTN" "ncWNT" "VEGF" "PTPRM" "CD99" "SEMA3"
## [19] "NECTIN" "PDGF" "APP" "IGF"
## Pathways for interaction 3 to 8 :
## pathway_name
## 1 COLLAGEN
## 2 SELE
## 3 LAMININ
## 4 VISFATIN
## 5 JAM
## 6 ANGPT
## 7 THBS
## 8 GALECTIN
## 9 SEMA4
## 10 CD99
## 11 SEMA6
## 12 NOTCH
## 13 PTPRM
## 14 FN1
## 15 EDN
## 16 TENASCIN
## 17 TGFb
## 18 PROS
## 19 PERIOSTIN
## 20 SEMA3
## 21 VCAM
## 22 CXCL
## 23 BMP
## 24 MIF
## 25 GAS
## 26 MPZ
## 27 EGF
## 28 PDGF
## 29 WNT
## Pathways in Tumor:
## [1] "COLLAGEN" "SELE" "LAMININ" "VISFATIN" "JAM" "ANGPT"
## [7] "THBS" "GALECTIN" "SEMA4" "CD99" "SEMA6" "NOTCH"
## [13] "PTPRM" "FN1" "EDN" "TENASCIN" "TGFb" "PROS"
## [19] "PERIOSTIN" "SEMA3" "VCAM" "CXCL" "BMP" "MIF"
## [25] "GAS" "MPZ" "EGF" "PDGF" "WNT"
## Pathways in Skin:
## [1] "COLLAGEN" "SELE" "LAMININ" "VISFATIN" "JAM" "ANGPT"
## [7] "THBS" "SEMA4" "CD99" "SEMA6" "NOTCH" "PTPRM"
## [13] "FN1" "EDN" "TENASCIN" "TGFb" "PROS" "PERIOSTIN"
## [19] "SEMA3" "VCAM" "CXCL" "BMP" "MIF" "GAS"
## [25] "MPZ" "EGF" "PDGF" "WNT"
## Pathways for interaction 8 to 13 :
## pathway_name
## 1 FN1
## 2 COLLAGEN
## 3 CD99
## 4 LAMININ
## 5 COMPLEMENT
## 6 TENASCIN
## 7 MK
## 8 THY1
## 9 MIF
## 10 THBS
## 11 CXCL
## 12 ANNEXIN
## 13 IL6
## 14 FGF
## 15 ANGPTL
## 16 GAS
## 17 CSF
## 18 MHC-I
## 19 SEMA3
## 20 SEMA4
## 21 MHC-II
## 22 JAM
## 23 MPZ
## 24 IL16
## 25 ICAM
## 26 PROS
## 27 NECTIN
## 28 PTN
## 29 APP
## 30 TGFb
## 31 VISFATIN
## 32 VEGF
## Pathways in Tumor:
## [1] "FN1" "COLLAGEN" "CD99" "LAMININ" "COMPLEMENT"
## [6] "TENASCIN" "MK" "THY1" "MIF" "THBS"
## [11] "CXCL" "ANNEXIN" "IL6" "FGF" "ANGPTL"
## [16] "GAS" "CSF" "MHC-I" "SEMA3" "SEMA4"
## [21] "MHC-II" "JAM" "MPZ" "IL16" "ICAM"
## [26] "PROS" "NECTIN" "PTN" "APP" "TGFb"
## [31] "VISFATIN" "VEGF"
## Pathways in Skin:
## [1] "FN1" "COLLAGEN" "CD99" "LAMININ" "COMPLEMENT"
## [6] "TENASCIN" "MK" "THY1" "MIF" "THBS"
## [11] "CXCL" "ANNEXIN" "IL6" "FGF" "ANGPTL"
## [16] "GAS" "CSF" "MHC-I" "SEMA3" "SEMA4"
## [21] "MHC-II" "JAM" "MPZ" "IL16" "ICAM"
## [26] "PROS" "NECTIN" "PTN" "APP" "TGFb"
## [31] "VISFATIN" "VEGF"
## Pathways for interaction 6 to 2 :
## pathway_name
## 1 COLLAGEN
## 2 LAMININ
## 3 CD99
## 4 VISFATIN
## 5 MIF
## 6 FN1
## 7 VEGF
## 8 CD46
## 9 SEMA4
## 10 ADGRE5
## 11 CCL
## 12 ESAM
## 13 PDGF
## 14 ANGPT
## 15 APP
## 16 PTPRM
## Pathways in Tumor:
## [1] "COLLAGEN" "LAMININ" "CD99" "VISFATIN" "MIF" "FN1"
## [7] "VEGF" "CD46" "SEMA4" "ADGRE5" "CCL" "ESAM"
## [13] "PDGF" "ANGPT" "APP" "PTPRM"
## Pathways in Skin:
## [1] "COLLAGEN" "LAMININ" "CD99" "VISFATIN" "MIF" "FN1"
## [7] "VEGF" "CD46" "SEMA4" "ADGRE5" "CCL" "ESAM"
## [13] "PDGF" "ANGPT" "APP" "PTPRM"
## Pathways for interaction 8 to 6 :
## pathway_name
## 1 LAMININ
## 2 MK
## 3 CD99
## 4 CD46
## 5 COLLAGEN
## 6 GAS
## 7 PERIOSTIN
## 8 THBS
## 9 VISFATIN
## 10 ncWNT
## 11 NEGR
## 12 CALCR
## 13 MPZ
## 14 HSPG
## 15 JAM
## 16 FN1
## 17 PTN
## 18 PROS
## 19 NECTIN
## 20 PDGF
## 21 CSF
## 22 PTPRM
## 23 BMP
## 24 EPHA
## 25 IGF
## Pathways in Tumor:
## [1] "LAMININ" "MK" "CD99" "CD46" "COLLAGEN" "GAS"
## [7] "PERIOSTIN" "THBS" "VISFATIN" "ncWNT" "NEGR" "CALCR"
## [13] "MPZ" "HSPG" "JAM" "FN1" "PTN" "PROS"
## [19] "NECTIN" "PDGF" "CSF" "PTPRM" "BMP" "EPHA"
## [25] "IGF"
## Pathways in Skin:
## [1] "LAMININ" "MK" "CD99" "CD46" "COLLAGEN" "GAS"
## [7] "PERIOSTIN" "THBS" "VISFATIN" "ncWNT" "NEGR" "CALCR"
## [13] "MPZ" "HSPG" "JAM" "FN1" "PTN" "PROS"
## [19] "NECTIN" "PDGF" "CSF" "PTPRM" "BMP" "EPHA"
## [25] "IGF"
## Pathways for interaction 5 to 2 :
## pathway_name
## 1 COLLAGEN
## 2 LAMININ
## 3 VISFATIN
## 4 FN1
## 5 ncWNT
## 6 SEMA4
## 7 CXCL
## 8 VEGF
## 9 ANGPTL
## 10 MIF
## 11 APP
## 12 CD46
## 13 SEMA3
## 14 PTN
## 15 MK
## 16 CCL
## 17 NECTIN
## 18 PTPRM
## 19 APJ
## 20 CALCR
## 21 PDGF
## 22 CD99
## 23 IGF
## Pathways in Tumor:
## [1] "COLLAGEN" "LAMININ" "VISFATIN" "FN1" "ncWNT" "SEMA4"
## [7] "CXCL" "VEGF" "ANGPTL" "MIF" "APP" "CD46"
## [13] "SEMA3" "PTN" "MK" "CCL" "NECTIN" "PTPRM"
## [19] "APJ" "CALCR" "PDGF" "CD99" "IGF"
## Pathways in Skin:
## [1] "COLLAGEN" "LAMININ" "VISFATIN" "FN1" "ncWNT" "SEMA4"
## [7] "CXCL" "VEGF" "ANGPTL" "MIF" "APP" "CD46"
## [13] "SEMA3" "PTN" "MK" "CCL" "NECTIN" "PTPRM"
## [19] "CALCR" "PDGF" "CD99" "IGF"
## Pathways for interaction 5 to 9 :
## pathway_name
## 1 COLLAGEN
## 2 THBS
## 3 LAMININ
## 4 ANGPTL
## 5 FGF
## 6 ncWNT
## 7 VISFATIN
## 8 SEMA4
## 9 IL6
## 10 NEGR
## 11 SEMA3
## 12 GAS
## 13 MPZ
## 14 FN1
## 15 CADM
## 16 TENASCIN
## 17 PTN
## 18 TGFb
## 19 JAM
## 20 MK
## 21 PROS
## 22 PTPRM
## 23 EPHA
## 24 NECTIN
## 25 CD46
## 26 PDGF
## 27 HSPG
## 28 CD99
## 29 MIF
## 30 PERIOSTIN
## 31 CXCL
## 32 IGF
## Pathways in Tumor:
## [1] "COLLAGEN" "THBS" "LAMININ" "ANGPTL" "FGF" "ncWNT"
## [7] "VISFATIN" "SEMA4" "IL6" "NEGR" "SEMA3" "GAS"
## [13] "MPZ" "FN1" "CADM" "TENASCIN" "PTN" "TGFb"
## [19] "JAM" "MK" "PROS" "PTPRM" "EPHA" "NECTIN"
## [25] "CD46" "PDGF" "HSPG" "CD99" "MIF" "PERIOSTIN"
## [31] "CXCL" "IGF"
## Pathways in Skin:
## [1] "COLLAGEN" "THBS" "LAMININ" "ANGPTL" "FGF" "ncWNT"
## [7] "VISFATIN" "SEMA4" "IL6" "NEGR" "SEMA3" "GAS"
## [13] "MPZ" "FN1" "CADM" "TENASCIN" "PTN" "TGFb"
## [19] "JAM" "MK" "PROS" "PTPRM" "EPHA" "NECTIN"
## [25] "CD46" "PDGF" "HSPG" "CD99" "MIF" "PERIOSTIN"
## [31] "CXCL" "IGF"
## Pathways for interaction 2 to 2 :
## pathway_name
## 1 COLLAGEN
## 2 MIF
## 3 LAMININ
## 4 VISFATIN
## 5 CD99
## 6 SEMA4
## 7 FN1
## 8 PECAM1
## 9 CXCL
## 10 CD46
## 11 CCL
## 12 APP
## 13 ESAM
## 14 PTPRM
## 15 ANGPT
## 16 CDH5
## Pathways in Tumor:
## [1] "COLLAGEN" "MIF" "LAMININ" "VISFATIN" "CD99" "SEMA4"
## [7] "FN1" "PECAM1" "CXCL" "CD46" "CCL" "APP"
## [13] "ESAM" "PTPRM" "ANGPT" "CDH5"
## Pathways in Skin:
## [1] "COLLAGEN" "MIF" "LAMININ" "VISFATIN" "CD99" "SEMA4"
## [7] "FN1" "PECAM1" "CXCL" "CD46" "CCL" "APP"
## [13] "ESAM" "PTPRM" "ANGPT" "CDH5"# List of interactions
interactions <- list(
"Fibroblast_32 to Fibroblast_32" = list(
"tumor" = c("COLLAGEN", "NEGR", "MK", "LAMININ", "TENASCIN", "SEMA4", "FN1", "VISFATIN", "FGF", "THBS", "ncWNT", "ANGPTL", "TGFb", "GAS", "CD99", "PTPRM", "JAM", "CXCL", "PERIOSTIN", "SEMA3", "PROS", "CADM", "PDGF", "CNTN", "PTN", "NECTIN", "TWEAK", "BMP", "MIF", "MPZ", "IGF", "WNT"),
"skin" = c("COLLAGEN", "NEGR", "MK", "LAMININ", "TENASCIN", "SEMA4", "FN1", "VISFATIN", "FGF", "THBS", "ncWNT", "ANGPTL", "TGFb", "GAS", "CD99", "PTPRM", "JAM", "CXCL", "PERIOSTIN", "SEMA3", "PROS", "CADM", "PDGF", "PTN", "NECTIN", "TWEAK", "BMP", "MIF", "MPZ", "IGF", "WNT")
),
"Fibroblast_36 to Fibroblast_36" = list(
"tumor" = c("COLLAGEN", "ANGPTL", "LAMININ", "MK", "THBS", "MPZ", "VISFATIN", "JAM", "NEGR", "IL6", "SEMA3", "FN1", "SEMA4", "FGF", "GAS", "TENASCIN", "ADGRE5", "PROS", "CXCL", "NOTCH", "CD46", "NECTIN", "PTN", "TWEAK", "CD99", "PERIOSTIN", "HSPG", "PTPRM", "EPHA", "TGFb", "PDGF", "EPHB", "CADM", "MIF", "IGF", "WNT"),
"skin" = c("COLLAGEN", "ANGPTL", "LAMININ", "MK", "THBS", "MPZ", "VISFATIN", "JAM", "NEGR", "IL6", "SEMA3", "FN1", "SEMA4", "FGF", "GAS", "TENASCIN", "ADGRE5", "PROS", "CXCL", "NOTCH", "CD46", "NECTIN", "PTN", "TWEAK", "CD99", "PERIOSTIN", "HSPG", "PTPRM", "EPHA", "TGFb", "PDGF", "EPHB", "CADM", "MIF", "IGF", "WNT")
),
"Fibroblast_32 to Endothel" = list(
"tumor" = c("COLLAGEN", "LAMININ", "MK", "VISFATIN", "MIF", "FN1", "CXCL", "SEMA4", "CALCR", "ANGPTL", "CD46", "CCL", "PTN", "ncWNT", "VEGF", "PTPRM", "CD99", "SEMA3", "NECTIN", "APJ", "PDGF", "APP", "IGF"),
"skin" = c("COLLAGEN", "LAMININ", "MK", "VISFATIN", "MIF", "FN1", "CXCL", "SEMA4", "CALCR", "ANGPTL", "CD46", "CCL", "PTN", "ncWNT", "VEGF", "PTPRM", "CD99", "SEMA3", "NECTIN", "PDGF", "APP", "IGF")
),
"Endothel_vasc._31 to Fibroblast_32" = list(
"tumor" = c("COLLAGEN", "SELE", "LAMININ", "VISFATIN", "JAM", "ANGPT", "THBS", "GALECTIN", "SEMA4", "CD99", "SEMA6", "NOTCH", "PTPRM", "FN1", "EDN", "TENASCIN", "TGFb", "PROS", "PERIOSTIN", "SEMA3", "VCAM", "CXCL", "BMP", "MIF", "GAS", "MPZ", "EGF", "PDGF", "WNT"),
"skin" = c("COLLAGEN", "SELE", "LAMININ", "VISFATIN", "JAM", "ANGPT", "THBS", "SEMA4", "CD99", "SEMA6", "NOTCH", "PTPRM", "FN1", "EDN", "TENASCIN", "TGFb", "PROS", "PERIOSTIN", "SEMA3", "VCAM", "CXCL", "BMP", "MIF", "GAS", "MPZ", "EGF", "PDGF", "WNT")
),
"Fibroblast_32 to Monocyte" = list(
"tumor" = c("FN1", "COLLAGEN", "CD99", "LAMININ", "COMPLEMENT", "TENASCIN", "MK", "THY1", "MIF", "THBS", "CXCL", "ANNEXIN", "IL6", "FGF", "ANGPTL", "GAS", "CSF", "MHC-I", "SEMA3", "SEMA4", "MHC-II", "JAM", "MPZ", "IL16", "ICAM", "PROS", "NECTIN", "PTN", "APP", "TGFb", "VISFATIN", "VEGF"),
"skin" = c("FN1", "COLLAGEN", "CD99", "LAMININ", "COMPLEMENT", "TENASCIN", "MK", "THY1", "MIF", "THBS", "CXCL", "ANNEXIN", "IL6", "FGF", "ANGPTL", "GAS", "CSF", "MHC-I", "SEMA3", "SEMA4", "MHC-II", "JAM", "MPZ", "IL16", "ICAM", "PROS", "NECTIN", "PTN", "APP", "TGFb", "VISFATIN", "VEGF")
),
"Fibroblast_20 to Endothel" = list(
"tumor" = c("COLLAGEN", "LAMININ", "CD99", "VISFATIN", "MIF", "FN1", "VEGF", "CD46", "SEMA4", "ADGRE5", "CCL", "ESAM", "PDGF", "ANGPT", "APP", "PTPRM"),
"skin" = c("COLLAGEN", "LAMININ", "CD99", "VISFATIN", "MIF", "FN1", "VEGF", "CD46", "SEMA4", "ADGRE5", "CCL", "ESAM", "PDGF", "ANGPT", "APP", "PTPRM")
),
"Fibroblast_32 to Fibroblast_20" = list(
"tumor" = c("LAMININ", "MK", "CD99", "CD46", "COLLAGEN", "GAS", "PERIOSTIN", "THBS", "VISFATIN", "ncWNT", "NEGR", "CALCR", "MPZ", "HSPG", "JAM", "FN1", "PTN", "PROS", "NECTIN", "PDGF", "CSF", "PTPRM", "BMP", "EPHA", "IGF"),
"skin" = c("LAMININ", "MK", "CD99", "CD46", "COLLAGEN", "GAS", "PERIOSTIN", "THBS", "VISFATIN", "ncWNT", "NEGR", "CALCR", "MPZ", "HSPG", "JAM", "FN1", "PTN", "PROS", "NECTIN", "PDGF", "CSF", "PTPRM", "BMP", "EPHA", "IGF")
),
"Fibroblast_18 to Endothel" = list(
"tumor" = c("COLLAGEN", "LAMININ", "VISFATIN", "FN1", "ncWNT", "SEMA4", "CXCL", "VEGF", "ANGPTL", "MIF", "APP", "CD46", "SEMA3", "PTN", "MK", "CCL", "NECTIN", "PTPRM", "APJ", "CALCR", "PDGF", "CD99", "IGF"),
"skin" = c("COLLAGEN", "LAMININ", "VISFATIN", "FN1", "ncWNT", "SEMA4", "CXCL", "VEGF", "ANGPTL", "MIF", "APP", "CD46", "SEMA3", "PTN", "MK", "CCL", "NECTIN", "PTPRM", "CALCR", "PDGF", "CD99", "IGF")
),
"Fibroblast_18 to Fibroblast_36" = list(
"tumor" = c("COLLAGEN", "THBS", "LAMININ", "ANGPTL", "FGF", "ncWNT", "VISFATIN", "SEMA4", "IL6", "NEGR", "SEMA3", "GAS", "MPZ", "FN1", "CADM", "TENASCIN", "PTN", "TGFb", "JAM", "MK", "PROS", "PTPRM", "EPHA", "NECTIN", "CD46", "PDGF", "HSPG", "CD99", "MIF", "PERIOSTIN", "CXCL", "IGF"),
"skin" = c("COLLAGEN", "THBS", "LAMININ", "ANGPTL", "FGF", "ncWNT", "VISFATIN", "SEMA4", "IL6", "NEGR", "SEMA3", "GAS", "MPZ", "FN1", "CADM", "TENASCIN", "PTN", "TGFb", "JAM", "MK", "PROS", "PTPRM", "EPHA", "NECTIN", "CD46", "PDGF", "HSPG", "CD99", "MIF", "PERIOSTIN", "CXCL", "IGF")
),
"Endothel to Endothel" = list(
"tumor" = c("COLLAGEN", "MIF", "LAMININ", "VISFATIN", "CD99", "SEMA4", "FN1", "PECAM1", "CXCL", "CD46", "CCL", "APP", "ESAM", "PTPRM", "ANGPT", "CDH5"),
"skin" = c("COLLAGEN", "MIF", "LAMININ", "VISFATIN", "CD99", "SEMA4", "FN1", "PECAM1", "CXCL", "CD46", "CCL", "APP", "ESAM", "PTPRM", "ANGPT", "CDH5")
)
)
# Find common pathways for each interaction pair
common_pathways_each_pair <- lapply(interactions, function(x) {
intersect(x$tumor, x$skin)
})
# Find common pathways across all interaction pairs
common_pathways_across_all <- Reduce(intersect, common_pathways_each_pair)
# Print common pathways across all interaction pairs
cat("Common pathways across all interaction pairs:\n")## Common pathways across all interaction pairs:print(common_pathways_across_all)## [1] "COLLAGEN" "LAMININ" "FN1" "VISFATIN" "CD99"# Find pathways that are present in either tumor OR skin for each interaction pair
all_pathways_each_pair <- lapply(interactions, function(x) {
union(x$tumor, x$skin)
})
# Print pathways for each interaction pair
for (interaction in names(all_pathways_each_pair)) {
cat("Pathways for interaction", interaction, ":\n")
print(all_pathways_each_pair[[interaction]])
cat("\n")
}## Pathways for interaction Fibroblast_32 to Fibroblast_32 :
## [1] "COLLAGEN" "NEGR" "MK" "LAMININ" "TENASCIN" "SEMA4"
## [7] "FN1" "VISFATIN" "FGF" "THBS" "ncWNT" "ANGPTL"
## [13] "TGFb" "GAS" "CD99" "PTPRM" "JAM" "CXCL"
## [19] "PERIOSTIN" "SEMA3" "PROS" "CADM" "PDGF" "CNTN"
## [25] "PTN" "NECTIN" "TWEAK" "BMP" "MIF" "MPZ"
## [31] "IGF" "WNT"
##
## Pathways for interaction Fibroblast_36 to Fibroblast_36 :
## [1] "COLLAGEN" "ANGPTL" "LAMININ" "MK" "THBS" "MPZ"
## [7] "VISFATIN" "JAM" "NEGR" "IL6" "SEMA3" "FN1"
## [13] "SEMA4" "FGF" "GAS" "TENASCIN" "ADGRE5" "PROS"
## [19] "CXCL" "NOTCH" "CD46" "NECTIN" "PTN" "TWEAK"
## [25] "CD99" "PERIOSTIN" "HSPG" "PTPRM" "EPHA" "TGFb"
## [31] "PDGF" "EPHB" "CADM" "MIF" "IGF" "WNT"
##
## Pathways for interaction Fibroblast_32 to Endothel :
## [1] "COLLAGEN" "LAMININ" "MK" "VISFATIN" "MIF" "FN1"
## [7] "CXCL" "SEMA4" "CALCR" "ANGPTL" "CD46" "CCL"
## [13] "PTN" "ncWNT" "VEGF" "PTPRM" "CD99" "SEMA3"
## [19] "NECTIN" "APJ" "PDGF" "APP" "IGF"
##
## Pathways for interaction Endothel_vasc._31 to Fibroblast_32 :
## [1] "COLLAGEN" "SELE" "LAMININ" "VISFATIN" "JAM" "ANGPT"
## [7] "THBS" "GALECTIN" "SEMA4" "CD99" "SEMA6" "NOTCH"
## [13] "PTPRM" "FN1" "EDN" "TENASCIN" "TGFb" "PROS"
## [19] "PERIOSTIN" "SEMA3" "VCAM" "CXCL" "BMP" "MIF"
## [25] "GAS" "MPZ" "EGF" "PDGF" "WNT"
##
## Pathways for interaction Fibroblast_32 to Monocyte :
## [1] "FN1" "COLLAGEN" "CD99" "LAMININ" "COMPLEMENT"
## [6] "TENASCIN" "MK" "THY1" "MIF" "THBS"
## [11] "CXCL" "ANNEXIN" "IL6" "FGF" "ANGPTL"
## [16] "GAS" "CSF" "MHC-I" "SEMA3" "SEMA4"
## [21] "MHC-II" "JAM" "MPZ" "IL16" "ICAM"
## [26] "PROS" "NECTIN" "PTN" "APP" "TGFb"
## [31] "VISFATIN" "VEGF"
##
## Pathways for interaction Fibroblast_20 to Endothel :
## [1] "COLLAGEN" "LAMININ" "CD99" "VISFATIN" "MIF" "FN1"
## [7] "VEGF" "CD46" "SEMA4" "ADGRE5" "CCL" "ESAM"
## [13] "PDGF" "ANGPT" "APP" "PTPRM"
##
## Pathways for interaction Fibroblast_32 to Fibroblast_20 :
## [1] "LAMININ" "MK" "CD99" "CD46" "COLLAGEN" "GAS"
## [7] "PERIOSTIN" "THBS" "VISFATIN" "ncWNT" "NEGR" "CALCR"
## [13] "MPZ" "HSPG" "JAM" "FN1" "PTN" "PROS"
## [19] "NECTIN" "PDGF" "CSF" "PTPRM" "BMP" "EPHA"
## [25] "IGF"
##
## Pathways for interaction Fibroblast_18 to Endothel :
## [1] "COLLAGEN" "LAMININ" "VISFATIN" "FN1" "ncWNT" "SEMA4"
## [7] "CXCL" "VEGF" "ANGPTL" "MIF" "APP" "CD46"
## [13] "SEMA3" "PTN" "MK" "CCL" "NECTIN" "PTPRM"
## [19] "APJ" "CALCR" "PDGF" "CD99" "IGF"
##
## Pathways for interaction Fibroblast_18 to Fibroblast_36 :
## [1] "COLLAGEN" "THBS" "LAMININ" "ANGPTL" "FGF" "ncWNT"
## [7] "VISFATIN" "SEMA4" "IL6" "NEGR" "SEMA3" "GAS"
## [13] "MPZ" "FN1" "CADM" "TENASCIN" "PTN" "TGFb"
## [19] "JAM" "MK" "PROS" "PTPRM" "EPHA" "NECTIN"
## [25] "CD46" "PDGF" "HSPG" "CD99" "MIF" "PERIOSTIN"
## [31] "CXCL" "IGF"
##
## Pathways for interaction Endothel to Endothel :
## [1] "COLLAGEN" "MIF" "LAMININ" "VISFATIN" "CD99" "SEMA4"
## [7] "FN1" "PECAM1" "CXCL" "CD46" "CCL" "APP"
## [13] "ESAM" "PTPRM" "ANGPT" "CDH5"# Find unique pathways across all interaction pairs
all_unique_pathways <- unique(unlist(all_pathways_each_pair))
# Print all unique pathways across all interaction pairs
cat("All unique pathways across all interaction pairs:\n")## All unique pathways across all interaction pairs:print(all_unique_pathways)## [1] "COLLAGEN" "NEGR" "MK" "LAMININ" "TENASCIN"
## [6] "SEMA4" "FN1" "VISFATIN" "FGF" "THBS"
## [11] "ncWNT" "ANGPTL" "TGFb" "GAS" "CD99"
## [16] "PTPRM" "JAM" "CXCL" "PERIOSTIN" "SEMA3"
## [21] "PROS" "CADM" "PDGF" "CNTN" "PTN"
## [26] "NECTIN" "TWEAK" "BMP" "MIF" "MPZ"
## [31] "IGF" "WNT" "IL6" "ADGRE5" "NOTCH"
## [36] "CD46" "HSPG" "EPHA" "EPHB" "CALCR"
## [41] "CCL" "VEGF" "APJ" "APP" "SELE"
## [46] "ANGPT" "GALECTIN" "SEMA6" "EDN" "VCAM"
## [51] "EGF" "COMPLEMENT" "THY1" "ANNEXIN" "CSF"
## [56] "MHC-I" "MHC-II" "IL16" "ICAM" "ESAM"
## [61] "PECAM1" "CDH5"Violin plots
Here I create new graphs for abs(Interaction_Difference_abs) top10 interactions.
# Filter to get the top 10 interactions by absolute difference
top_10_diff <- merged_df.interactions%>%
dplyr::ungroup() %>% # Calculate differences without grouping by 'source'
dplyr::arrange(-abs(Interaction_Difference_abs)) %>%
dplyr::slice_head(n = 10)
print(top_10_diff)## # A tibble: 10 × 6
## source target Tumor_Interactions Skin_Interactions Interaction_Difference
## <fct> <fct> <int> <int> <int>
## 1 Fibroblas… Kerat… 74 74 0
## 2 Fibroblas… Fibro… 71 111 -40
## 3 Fibroblas… Kerat… 65 87 -22
## 4 Fibroblas… Fibro… 75 84 -9
## 5 Fibroblas… T fh 65 56 9
## 6 Fibroblas… Kerat… 61 56 5
## 7 Endothel_… T fh 56 59 -3
## 8 Schwann_43 Kerat… 45 56 -11
## 9 Fibroblas… Kerat… 66 80 -14
## 10 Endothel Kerat… 50 34 16
## # ℹ 1 more variable: Interaction_Difference_abs <int># Plot top 10 interactions with biggest differences
difference_plot <- ggplot(
top_10_diff,
aes(
x = paste(source, target, sep = "-"),
y = Interaction_Difference_abs,
fill = Interaction_Difference_abs > 0)
) +
geom_bar(
stat = "identity",
position = "dodge"
) +
scale_fill_manual(
values = c(
"TRUE" = rgb(178/255, 24/255, 43/255),
"FALSE" = rgb(33/255, 102/255, 172/255)
),
labels = c(
"TRUE" = "Tumor",
"FALSE" = "Skin")
) +
theme_minimal() +
labs(
title = "Top 10 according to Interaction_Difference_abs (Tumor - Skin)",
y = "Difference in Interactions",
x = "Interaction (Source-target)") +
theme(axis.text.x = element_text(
angle = 90,
hjust = 1)
)
print(difference_plot)
ggsave("~/rocker/RDEB/thesis/Top_10_Interaction_Difference_abs.png",
plot = difference_plot,
width = 10,
height = 8,
dpi = 300)
# Now, let's loop over these top 10 interactions and create the desired plots.
for (i in 1:nrow(top_10_diff)) {
current_source <- top_10_diff$source[i]
current_target <- top_10_diff$target[i]
# Filter the merged_data for the current pair.
current_data <- merged_data %>%
filter(source == current_source,
target == current_target)
# Plot
p <- ggplot(
current_data,
aes(
x = ligand,
y = receptor,
fill = prob.delta)
) +
geom_tile() +
scale_fill_gradient2(
low = rgb(33/255, 102/255, 172/255),
high = rgb(178/255, 24/255, 43/255),
mid = "grey",
midpoint = 0,
limits = c(min(current_data$prob.delta, na.rm = TRUE),
max(current_data$prob.delta, na.rm = TRUE)),
name = "Prob Delta") +
labs(title = paste("Ligand-Receptor Interactions for",
current_source,
"to",
current_target),
x = "Ligand",
y = "Receptor"
) +
theme_minimal() +
theme(axis.text.x = element_text(
angle = 90,
vjust = 0.5
),
axis.text.y = element_text(hjust = 1))
print(p)
# Save the plot
file_name <- paste0("~/rocker/RDEB/thesis/interaction_plots_abs/",
current_source,
"_to_",
current_target,
"_abs_",
".pdf"
)
ggsave(
file_name,
plot = p,
width = 10,
height = 10
)
# Extracting the relevant interactions from merged_data for the current interaction pair
filtered_data <- current_data %>%
distinct(pathway_name) # Getting unique pathway names involved in these interactions
# Print the pathways involved in the current interaction pair
cat("Pathways for interaction", current_source, "to", current_target, ":\n")
print(filtered_data)
# Check if these pathways are in the provided pathways lists
pathways_involved_t <- filtered_data$pathway_name %in% pathways.show.t
pathways_involved_s <- filtered_data$pathway_name %in% pathways.show.s
# Print pathways involved both in tumor and skin for the current interaction pair
cat("Pathways in Tumor:\n")
print(filtered_data$pathway_name[pathways_involved_t])
cat("Pathways in Skin:\n")
print(filtered_data$pathway_name[pathways_involved_s])
}
## Pathways for interaction 8 to 11 :
## pathway_name
## 1 COLLAGEN
## 2 LAMININ
## 3 FN1
## 4 MIF
## 5 THBS
## 6 MK
## 7 VISFATIN
## 8 APP
## 9 CD99
## 10 TENASCIN
## 11 ncWNT
## 12 PTN
## 13 CD46
## 14 JAM
## 15 MPZ
## 16 IGF
## Pathways in Tumor:
## [1] "COLLAGEN" "LAMININ" "FN1" "MIF" "THBS" "MK"
## [7] "VISFATIN" "APP" "CD99" "TENASCIN" "ncWNT" "PTN"
## [13] "CD46" "JAM" "MPZ" "IGF"
## Pathways in Skin:
## [1] "COLLAGEN" "LAMININ" "FN1" "MIF" "THBS" "MK"
## [7] "VISFATIN" "APP" "CD99" "TENASCIN" "ncWNT" "PTN"
## [13] "CD46" "JAM" "MPZ" "IGF"
## Pathways for interaction 9 to 9 :
## pathway_name
## 1 COLLAGEN
## 2 ANGPTL
## 3 LAMININ
## 4 MK
## 5 THBS
## 6 MPZ
## 7 VISFATIN
## 8 JAM
## 9 NEGR
## 10 IL6
## 11 SEMA3
## 12 FN1
## 13 SEMA4
## 14 FGF
## 15 GAS
## 16 TENASCIN
## 17 ADGRE5
## 18 PROS
## 19 CXCL
## 20 NOTCH
## 21 CD46
## 22 NECTIN
## 23 PTN
## 24 TWEAK
## 25 CD99
## 26 PERIOSTIN
## 27 HSPG
## 28 PTPRM
## 29 EPHA
## 30 TGFb
## 31 PDGF
## 32 EPHB
## 33 CADM
## 34 MIF
## 35 IGF
## 36 WNT
## Pathways in Tumor:
## [1] "COLLAGEN" "ANGPTL" "LAMININ" "MK" "THBS" "MPZ"
## [7] "VISFATIN" "JAM" "NEGR" "IL6" "SEMA3" "FN1"
## [13] "SEMA4" "FGF" "GAS" "TENASCIN" "ADGRE5" "PROS"
## [19] "CXCL" "NOTCH" "CD46" "NECTIN" "PTN" "TWEAK"
## [25] "CD99" "PERIOSTIN" "HSPG" "PTPRM" "EPHA" "TGFb"
## [31] "PDGF" "EPHB" "CADM" "MIF" "IGF" "WNT"
## Pathways in Skin:
## [1] "COLLAGEN" "ANGPTL" "LAMININ" "MK" "THBS" "MPZ"
## [7] "VISFATIN" "JAM" "NEGR" "IL6" "SEMA3" "FN1"
## [13] "SEMA4" "FGF" "GAS" "TENASCIN" "ADGRE5" "PROS"
## [19] "CXCL" "NOTCH" "CD46" "NECTIN" "PTN" "TWEAK"
## [25] "CD99" "PERIOSTIN" "HSPG" "PTPRM" "EPHA" "TGFb"
## [31] "PDGF" "EPHB" "CADM" "MIF" "IGF" "WNT"
## Pathways for interaction 9 to 11 :
## pathway_name
## 1 COLLAGEN
## 2 THBS
## 3 FN1
## 4 LAMININ
## 5 MIF
## 6 MK
## 7 APP
## 8 TENASCIN
## 9 VISFATIN
## 10 PTN
## 11 JAM
## 12 CD46
## 13 MPZ
## 14 CD99
## 15 IGF
## Pathways in Tumor:
## [1] "COLLAGEN" "THBS" "FN1" "LAMININ" "MIF" "MK"
## [7] "APP" "TENASCIN" "VISFATIN" "PTN" "JAM" "CD46"
## [13] "MPZ" "CD99" "IGF"
## Pathways in Skin:
## [1] "COLLAGEN" "THBS" "FN1" "LAMININ" "MIF" "MK"
## [7] "APP" "TENASCIN" "VISFATIN" "PTN" "JAM" "CD46"
## [13] "MPZ" "CD99" "IGF"
## Pathways for interaction 8 to 9 :
## pathway_name
## 1 COLLAGEN
## 2 MK
## 3 LAMININ
## 4 THBS
## 5 NEGR
## 6 FGF
## 7 VISFATIN
## 8 IL6
## 9 ncWNT
## 10 TGFb
## 11 SEMA4
## 12 JAM
## 13 FN1
## 14 TENASCIN
## 15 CADM
## 16 CXCL
## 17 GAS
## 18 MPZ
## 19 PTPRM
## 20 PTN
## 21 PERIOSTIN
## 22 PROS
## 23 ANGPTL
## 24 SEMA3
## 25 HSPG
## 26 TWEAK
## 27 PDGF
## 28 EPHA
## 29 NECTIN
## 30 CD46
## 31 MIF
## 32 CD99
## 33 BMP
## 34 IGF
## 35 WNT
## Pathways in Tumor:
## [1] "COLLAGEN" "MK" "LAMININ" "THBS" "NEGR" "FGF"
## [7] "VISFATIN" "IL6" "ncWNT" "TGFb" "SEMA4" "JAM"
## [13] "FN1" "TENASCIN" "CADM" "CXCL" "GAS" "MPZ"
## [19] "PTPRM" "PTN" "PERIOSTIN" "PROS" "ANGPTL" "SEMA3"
## [25] "HSPG" "TWEAK" "PDGF" "EPHA" "NECTIN" "CD46"
## [31] "MIF" "CD99" "BMP" "IGF" "WNT"
## Pathways in Skin:
## [1] "COLLAGEN" "MK" "LAMININ" "THBS" "NEGR" "FGF"
## [7] "VISFATIN" "IL6" "ncWNT" "TGFb" "SEMA4" "JAM"
## [13] "FN1" "TENASCIN" "CADM" "CXCL" "GAS" "MPZ"
## [19] "PTPRM" "PTN" "PERIOSTIN" "PROS" "ANGPTL" "SEMA3"
## [25] "HSPG" "TWEAK" "PDGF" "EPHA" "NECTIN" "CD46"
## [31] "MIF" "CD99" "BMP" "IGF" "WNT"
## Pathways for interaction 8 to 24 :
## pathway_name
## 1 MK
## 2 LAMININ
## 3 COLLAGEN
## 4 THBS
## 5 IL2
## 6 THY1
## 7 FN1
## 8 CXCL
## 9 IL6
## 10 MHC-I
## 11 ICAM
## 12 CLEC
## 13 PTPRM
## 14 CD99
## 15 JAM
## 16 PTN
## 17 CADM
## 18 MIF
## 19 NECTIN
## 20 IL16
## 21 TRAIL
## 22 APP
## 23 TGFb
## 24 BMP
## 25 EPHA
## Pathways in Tumor:
## [1] "MK" "LAMININ" "COLLAGEN" "THBS" "IL2" "THY1"
## [7] "FN1" "CXCL" "IL6" "MHC-I" "ICAM" "CLEC"
## [13] "PTPRM" "CD99" "JAM" "PTN" "CADM" "MIF"
## [19] "NECTIN" "IL16" "TRAIL" "APP" "TGFb" "BMP"
## [25] "EPHA"
## Pathways in Skin:
## [1] "MK" "LAMININ" "COLLAGEN" "THBS" "IL2" "THY1"
## [7] "FN1" "CXCL" "IL6" "MHC-I" "ICAM" "CLEC"
## [13] "PTPRM" "CD99" "JAM" "PTN" "CADM" "MIF"
## [19] "NECTIN" "IL16" "TRAIL" "APP" "TGFb" "BMP"
## [25] "EPHA"
## Pathways for interaction 6 to 11 :
## pathway_name
## 1 COLLAGEN
## 2 LAMININ
## 3 MIF
## 4 FN1
## 5 CD99
## 6 VISFATIN
## 7 THBS
## 8 CD46
## 9 APP
## 10 JAM
## 11 ADGRE5
## 12 TENASCIN
## 13 MPZ
## Pathways in Tumor:
## [1] "COLLAGEN" "LAMININ" "MIF" "FN1" "CD99" "VISFATIN"
## [7] "THBS" "CD46" "APP" "JAM" "ADGRE5" "TENASCIN"
## [13] "MPZ"
## Pathways in Skin:
## [1] "COLLAGEN" "LAMININ" "MIF" "FN1" "CD99" "VISFATIN"
## [7] "THBS" "CD46" "APP" "JAM" "ADGRE5" "TENASCIN"
## [13] "MPZ"
## Pathways for interaction 3 to 24 :
## pathway_name
## 1 SELE
## 2 LAMININ
## 3 COLLAGEN
## 4 THBS
## 5 ICAM
## 6 GALECTIN
## 7 PECAM1
## 8 NECTIN
## 9 CD99
## 10 CXCL
## 11 MHC-II
## 12 ALCAM
## 13 TRAIL
## 14 PTPRM
## 15 FN1
## 16 CLEC
## 17 BMP
## 18 JAM
## 19 TGFb
## 20 NOTCH
## 21 IL6
## 22 MHC-I
## 23 MIF
## 24 APP
## 25 EPHB
## 26 EPHA
## Pathways in Tumor:
## [1] "SELE" "LAMININ" "COLLAGEN" "THBS" "ICAM" "GALECTIN"
## [7] "PECAM1" "NECTIN" "CD99" "CXCL" "MHC-II" "ALCAM"
## [13] "TRAIL" "PTPRM" "FN1" "CLEC" "BMP" "JAM"
## [19] "TGFb" "NOTCH" "IL6" "MHC-I" "MIF" "APP"
## [25] "EPHB" "EPHA"
## Pathways in Skin:
## [1] "SELE" "LAMININ" "COLLAGEN" "THBS" "ICAM" "PECAM1"
## [7] "NECTIN" "CD99" "CXCL" "MHC-II" "ALCAM" "TRAIL"
## [13] "PTPRM" "FN1" "CLEC" "BMP" "JAM" "TGFb"
## [19] "NOTCH" "IL6" "MHC-I" "MIF" "APP" "EPHB"
## [25] "EPHA"
## Pathways for interaction 22 to 11 :
## pathway_name
## 1 COLLAGEN
## 2 RELN
## 3 FN1
## 4 LAMININ
## 5 PTN
## 6 APP
## 7 VISFATIN
## 8 TENASCIN
## 9 MPZ
## 10 JAM
## 11 THBS
## 12 EGF
## 13 CD46
## Pathways in Tumor:
## [1] "COLLAGEN" "RELN" "FN1" "LAMININ" "PTN" "APP"
## [7] "VISFATIN" "TENASCIN" "MPZ" "JAM" "THBS" "EGF"
## [13] "CD46"
## Pathways in Skin:
## [1] "COLLAGEN" "FN1" "LAMININ" "PTN" "APP" "VISFATIN"
## [7] "TENASCIN" "MPZ" "JAM" "THBS" "EGF" "CD46"
## Pathways for interaction 5 to 11 :
## pathway_name
## 1 COLLAGEN
## 2 LAMININ
## 3 FN1
## 4 THBS
## 5 VISFATIN
## 6 APP
## 7 TENASCIN
## 8 PTN
## 9 MK
## 10 CD46
## 11 JAM
## 12 MPZ
## 13 CD99
## 14 IGF
## Pathways in Tumor:
## [1] "COLLAGEN" "LAMININ" "FN1" "THBS" "VISFATIN" "APP"
## [7] "TENASCIN" "PTN" "MK" "CD46" "JAM" "MPZ"
## [13] "CD99" "IGF"
## Pathways in Skin:
## [1] "COLLAGEN" "LAMININ" "FN1" "THBS" "VISFATIN" "APP"
## [7] "TENASCIN" "PTN" "MK" "CD46" "JAM" "MPZ"
## [13] "CD99" "IGF"
## Pathways for interaction 2 to 11 :
## pathway_name
## 1 COLLAGEN
## 2 MIF
## 3 SELE
## 4 APP
## 5 LAMININ
## 6 CD99
## 7 FN1
## 8 THBS
## 9 EGF
## 10 CD46
## Pathways in Tumor:
## [1] "COLLAGEN" "MIF" "SELE" "APP" "LAMININ" "CD99"
## [7] "FN1" "THBS" "EGF" "CD46"
## Pathways in Skin:
## [1] "COLLAGEN" "MIF" "SELE" "APP" "LAMININ" "CD99"
## [7] "FN1" "THBS" "EGF" "CD46"